LAUSR

Abstract Polycyclic aromatic hydrocarbons (PAHs) are Canceriogenic and mutagenic substances. These compounds are released in the environment by anthropogenic and natural sources. In this work, an adaptive neuro-fuzzy inference system (ANFIS) was employed to model the PAHs formation in sea sediment. Development of ANFIS model is on the basis of the Gaussian membership function. The result obtained by ANFIS model was analyzed with the statistical parameters such as mean squared error (MSE), mean absolute error percent (MEAEP), maximum absolute error percent (MAAEP) and R2. The prediction capability of ANFIS model was compared with the previous developed models. According to results obtained by statistical parameters, the ANFIS model has the best performance in estimating of PAHs with the lowest error values.